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local Copy, parent = torch.class('nn.Copy', 'nn.Module')
function Copy:__init(intype, outtype, forceCopy, dontCast)
intype = intype or torch.Tensor.__typename
outtype = outtype or torch.Tensor.__typename
self.dontCast = dontCast
parent.__init(self)
self.gradInput = torch.getmetatable(intype).new()
self.output = torch.getmetatable(outtype).new()
if (not forceCopy) and intype == outtype then
self.updateOutput = function(self, input)
self.output:set(input)
return input
end
self.updateGradInput = function(self, input, gradOutput)
self.gradInput:set(gradOutput)
return gradOutput
end
end
end
function Copy:updateOutput(input)
self.output:resize(input:size()):copy(input)
return self.output
end
function Copy:updateGradInput(input, gradOutput)
self.gradInput:resize(gradOutput:size()):copy(gradOutput)
return self.gradInput
end
function Copy:type(type, tensorCache)
if type and self.dontCast then
return self
end
return parent.type(self, type, tensorCache)
end
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